Load packages.

library(tidyverse)
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## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
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## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(ggmap)
## ℹ Google's Terms of Service: <https://mapsplatform.google.com>
##   Stadia Maps' Terms of Service: <https://stadiamaps.com/terms-of-service/>
##   OpenStreetMap's Tile Usage Policy: <https://operations.osmfoundation.org/policies/tiles/>
## ℹ Please cite ggmap if you use it! Use `citation("ggmap")` for details.
library(geosphere)
library(lubridate)
library(plotly)
## 
## Attaching package: 'plotly'
## 
## The following object is masked from 'package:ggmap':
## 
##     wind
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##     last_plot
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##     layout

Load data.

elk = read_csv("./data/elk.csv")
## Rows: 104913 Columns: 7
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (7): elk_id, year, month, day, hour, lat, long
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
raw_weather <- read_csv("./data/raw_weather_data.csv")
## Warning: One or more parsing issues, call `problems()` on your data frame for details,
## e.g.:
##   dat <- vroom(...)
##   problems(dat)
## Rows: 54745 Columns: 31
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr   (2): STATION, NAME
## dbl  (21): LATITUDE, LONGITUDE, ELEVATION, AWND, DAPR, MDPR, PRCP, SNOW, SNW...
## lgl   (7): MDSF, WT02, WT03, WT04, WT05, WT06, WT11
## date  (1): DATE
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
weather_stations <-
  raw_weather |>
  group_by(NAME, LATITUDE, LONGITUDE) |>
  summarize(n_obs = n())
## `summarise()` has grouped output by 'NAME', 'LATITUDE'. You can override using
## the `.groups` argument.
potential_stations <- 
  c("LEWIS LAKE DIVIDE, WY US", "SNAKE RIVER, WY US", "SNAKE RIVER STATION, WY US", "BASE CAMP, WY US", 
    "MORAN 5 WNW, WY US", "JACKSON 29.9 NNE, WY US", "BURRO HILL WYOMING, WY US", "MOOSE 1 NNE, WY US", 
    "MOOSE, WY US", "MOOSE .4 S, WY US", "JACKSON 12.3 NE, WY US", "JACKSON 12.2 NE, WY US", 
    "JACKSON HOLE AIRPORT, WY US", "JACKSON, WY US")

four_stations <- 
  c("SNAKE RIVER STATION, WY US", "MORAN 5 WNW, WY US", "BURRO HILL WYOMING, WY US", "MOOSE 1 NNE, WY US")

reduced_weather_stations <- 
  raw_weather |> 
  filter(NAME %in% four_stations) |> 
  group_by(NAME, LATITUDE, LONGITUDE) |> 
  summarize(n_obs = n()) |> 
  arrange(desc(n_obs))
## `summarise()` has grouped output by 'NAME', 'LATITUDE'. You can override using
## the `.groups` argument.
reduced_weather <- 
  raw_weather |> 
  filter(NAME %in% four_stations)

all_data <- read_csv("./data/all_data.csv")
## Rows: 104913 Columns: 16
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl  (15): elk_id, year, month, day, hour, lat, long, dist_km, land_cover, t...
## dttm  (1): dt
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
daily_elk =
  all_data |>
  group_by(
    elk_id,
    year,
    month,
    day,
    tavg,
    prcp,
    snow,
    snwd
  ) |>
  summarize(
    dist_km = sum(dist_km, na.rm = TRUE), 
    land_cover = mean(land_cover, na.rm = TRUE)
  )
## `summarise()` has grouped output by 'elk_id', 'year', 'month', 'day', 'tavg',
## 'prcp', 'snow'. You can override using the `.groups` argument.

Precip plotly.

# point + line, separated by month and year
reduced_weather |> 
  select(c(STATION, NAME, LATITUDE, LONGITUDE, DATE, PRCP, SNOW, SNWD, TAVG)) |> 
  mutate(year = format(DATE, "%Y"), 
         month = format(DATE, "%m")) |> 
  group_by(NAME, year, month) |> 
  summarize(station_precip_total = sum(PRCP, na.rm = TRUE)) |> 
  group_by(year, month) |> 
  summarize(station_precip_total_avg = mean(station_precip_total, na.rm = TRUE)) |> 
  mutate(year_month = paste(year, month, sep = "-")) |> 
  plot_ly(
    x = ~month, y = ~station_precip_total_avg, color = ~year, group = ~year, type = 'scatter', mode = 'lines'
    )
## `summarise()` has grouped output by 'NAME', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Warning in plot_ly(mutate(summarize(group_by(summarize(group_by(mutate(select(reduced_weather, : The group argument has been deprecated. Use `group_by()` or split instead.
## See `help('plotly_data')` for examples
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
# year-month totals, separated by year
reduced_weather |> 
  select(c(STATION, NAME, LATITUDE, LONGITUDE, DATE, PRCP, SNOW, SNWD, TAVG)) |> 
  mutate(year = format(DATE, "%Y"), 
         month = format(DATE, "%m")) |> 
  group_by(NAME, year, month) |> 
  summarize(station_precip_total = sum(PRCP, na.rm = TRUE)) |> 
  group_by(year, month) |> 
  summarize(station_precip_total_avg = mean(station_precip_total, na.rm = TRUE)) |> 
  mutate(year_month = paste(year, month, sep = "-")) |> 
  plot_ly(
    x = ~year_month, y = ~station_precip_total_avg, color = ~as.factor(year), type = "bar"
    )
## `summarise()` has grouped output by 'NAME', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

Snowfall plotly.

# point + line
reduced_weather |> 
  select(c(STATION, NAME, LATITUDE, LONGITUDE, DATE, PRCP, SNOW, SNWD, TAVG)) |> 
  mutate(year = format(DATE, "%Y"), 
         month = format(DATE, "%m")) |> 
  group_by(NAME, year, month) |> 
  summarize(station_snowfall_total = sum(SNOW, na.rm = TRUE)) |> 
  group_by(year, month) |> 
  summarize(station_snowfall_total_avg = mean(station_snowfall_total, na.rm = TRUE)) |> 
  mutate(year_month = paste(year, month, sep = "-")) |> 
  plot_ly(
    x = ~month, y = ~station_snowfall_total_avg, color = ~as.factor(year), group = ~year, type = 'scatter', mode = 'lines'
    )
## `summarise()` has grouped output by 'NAME', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Warning in plot_ly(mutate(summarize(group_by(summarize(group_by(mutate(select(reduced_weather, : The group argument has been deprecated. Use `group_by()` or split instead.
## See `help('plotly_data')` for examples
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
# year-month totals by year
reduced_weather |> 
  select(c(STATION, NAME, LATITUDE, LONGITUDE, DATE, PRCP, SNOW, SNWD, TAVG)) |> 
  mutate(year = format(DATE, "%Y"), 
         month = format(DATE, "%m")) |> 
  group_by(NAME, year, month) |> 
  summarize(station_snowfall_total = sum(SNOW, na.rm = TRUE)) |> 
  group_by(year, month) |> 
  summarize(station_snowfall_total_avg = mean(station_snowfall_total, na.rm = TRUE)) |> 
  mutate(year_month = paste(year, month, sep = "-")) |> 
  plot_ly(
    x = ~year_month, y = ~station_snowfall_total_avg, color = ~year, type = 'bar'
    )
## `summarise()` has grouped output by 'NAME', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

Snow depth plotly.

# point + line
reduced_weather |> 
  select(c(STATION, NAME, LATITUDE, LONGITUDE, DATE, PRCP, SNOW, SNWD, TAVG)) |> 
  mutate(year = format(DATE, "%Y"), 
         month = format(DATE, "%m")) |> 
  group_by(NAME, year, month) |> 
  summarize(station_snowdepth_total = sum(SNWD, na.rm = TRUE)) |> 
  group_by(year, month) |> 
  summarize(station_snowdepth_total_avg = mean(station_snowdepth_total, na.rm = TRUE)) |> 
  mutate(year_month = paste(year, month, sep = "-")) |> 
  plot_ly(
    x = ~month, y = ~station_snowdepth_total_avg, color = ~as.factor(year), group = ~year, type = 'scatter', mode = 'lines'
    )
## `summarise()` has grouped output by 'NAME', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Warning in plot_ly(mutate(summarize(group_by(summarize(group_by(mutate(select(reduced_weather, : The group argument has been deprecated. Use `group_by()` or split instead.
## See `help('plotly_data')` for examples
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
# year-month totals
reduced_weather |> 
  select(c(STATION, NAME, LATITUDE, LONGITUDE, DATE, PRCP, SNOW, SNWD, TAVG)) |> 
  mutate(year = format(DATE, "%Y"), 
         month = format(DATE, "%m")) |> 
  group_by(NAME, year, month) |> 
  summarize(station_snowdepth_total = sum(SNWD, na.rm = TRUE)) |> 
  group_by(year, month) |> 
  summarize(station_snowdepth_total_avg = mean(station_snowdepth_total, na.rm = TRUE)) |> 
  mutate(year_month = paste(year, month, sep = "-")) |> 
  plot_ly(
    x = ~year_month, y = ~station_snowdepth_total_avg, color = ~year, type = 'bar'
  )
## `summarise()` has grouped output by 'NAME', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors